Memory Maintenance
Intelligent memory management for OpenClaw agents. Reviews daily notes, suggests MEMORY.md updates, maintains directory health, and auto-cleans old files. Recommended for agents wi…
Max Hutchinson
@maxlauriehutchinson
What This Skill Does
Reviews daily session notes, suggests updates to MEMORY.md, monitors directory health, and auto-archives old files for OpenClaw agents. Runs scheduled analysis and generates structured suggestions for human approval.
Replaces manually sifting through daily notes and deciding what to keep or discard by automating memory review, consolidation, and cleanup for agents with growing context footprints.
When to Use It
- Schedule nightly review of recent daily notes to surface key decisions for MEMORY.md
- Clean up fragmented or bloated memory directories before starting a new project
- Archive daily notes older than a week to keep the workspace focused
- Consolidate scattered session logs into a single, actionable memory summary
- Run a dry-run review to preview suggested changes before applying any edits
- Automate retention policy enforcement to delete or trash outdated archive files
Install
$ openclaw skills install @maxlauriehutchinson/memory-maintenanceMemory Maintenance Skill
Intelligent memory management for OpenClaw agents. Reviews daily notes, suggests MEMORY.md updates, maintains directory health, and auto-cleans old files.
Why This Exists
Agents wake up fresh every session. Without maintenance:
- Daily notes pile up and become unsearchable
- Important decisions get buried in old sessions
- Context windows fill with irrelevant history
- You repeat the same context-setting every day
This skill automates the tedious work of keeping your agent's memory organized and actionable.
Features
- Content Review: Analyzes daily notes and suggests MEMORY.md updates
- Directory Health: Monitors memory/ directory for naming issues, fragmentation, bloat
- Auto-Cleanup: Archives old reviews (7+ days) and enforces retention policy (30 days)
- Safe by Default: Content changes require approval; only safe maintenance auto-applies
Recommended Model
This skill works well with lightweight models. We recommend:
- Primary:
gemini-2.5-flash(fast, cost-effective) - Fallback:
gemini-2.5-flash-lite(if rate limits hit)
Both handle the structured output and analysis tasks efficiently.
Quick Start
# Install the skill
clawhub install memory-maintenance
# Configure (optional)
# Edit config/settings.json to customize schedule, retention, etc.
# Run manually
openclaw skill memory-maintenance run
# Or let it run automatically via cron (configured during install)
Architecture
Daily Session Notes (memory/YYYY-MM-DD.md)
↓
Review Agent (scheduled daily)
↓
Structured Suggestions (JSON)
↓
Human Review (markdown report)
↓
Approved Updates → MEMORY.md
↓
Auto-Cleanup (archive old files)
Workflow
-
Daily Review (23:00 by default)
- Scans configurable lookback period (default: 7 days)
- Checks memory/ directory health
- Generates suggestions via LLM
- Outputs structured JSON + human-readable markdown
-
Human Review
- Read
agents/memory/review-v2-YYYY-MM-DD.md - Approve/reject suggestions
- Read
-
Apply Changes
# Dry run (preview) openclaw skill memory-maintenance apply --dry-run 2026-02-05 # Apply safe changes (archiving, cleanup) openclaw skill memory-maintenance apply --safe 2026-02-05 # Apply all (requires confirmation) openclaw skill memory-maintenance apply --all 2026-02-05 -
Auto-Cleanup (runs after successful review)
- Archives reviews older than configured threshold
- Deletes archive files older than retention period
- Cleans up error logs
Configuration
Edit config/settings.json:
{
"schedule": {
"enabled": true,
"time": "23:00",
"timezone": "Europe/London"
},
"review": {
"lookback_days": 7,
"model": "gemini-2.5-flash",
"max_suggestions": 10
},
"maintenance": {
"archive_after_days": 7,
"retention_days": 30,
"consolidate_fragments": true,
"auto_archive_safe": true
},
"safety": {
"require_approval_for_content": true,
"require_approval_for_delete": true,
"trash_instead_of_delete": true
}
}
Safety
- Content suggestions: Never auto-applied (human review mandatory)
- Safe maintenance (archiving): Auto-applied with
--safe - Risky operations (delete, rename): Require
--all+ confirmation - Trash recovery: Deleted files go to
agents/memory/.trash/(recoverable for retention period)
Commands
# Run review manually
openclaw skill memory-maintenance review
# Apply changes
openclaw skill memory-maintenance apply [--dry-run|--safe|--all] DATE
# Run cleanup
openclaw skill memory-maintenance cleanup
# Check status
openclaw skill memory-maintenance status
# View stats
openclaw skill memory-maintenance stats
Integration with MEMORY.md
The skill suggests updates to standard MEMORY.md sections:
- Agent Identity and Core Preferences
- Infrastructure/Setup
- Memory Management
- Backup & Migration
- Contacts
- Scheduled Operations
- Content Creation & Projects
- Active Projects
Files
Output
agents/memory/review-v2-YYYY-MM-DD.json— Structured suggestionsagents/memory/review-v2-YYYY-MM-DD.md— Human-readable reportagents/memory/stats.json— Aggregate statistics
Archive
agents/memory/archive/YYYY-MM/— Monthly bucketsagents/memory/.trash/— Recoverable deletions
Requirements
- OpenClaw >= 2026.2.0
- Gemini CLI (
brew install gemini-cli) - jq (
brew install jq) - Gemini API key (from Google AI Studio)
Troubleshooting
"Gemini failed"
→ Check GEMINI_API_KEY is set in .env or environment
"No suggestions generated"
→ Check daily notes exist in memory/YYYY-MM-DD.md
→ Review error logs in agents/memory/error-*.txt
"Too many maintenance tasks"
→ Run openclaw skill memory-maintenance apply --safe to archive old files
→ Adjust archive_after_days in config
Author
Built by Max Hutchinson as part of an AI agent infrastructure exploration.
- GitHub: @MaxLaurieHutchinson
- Agent: Ash (OpenClaw)
License
MIT — Free to use, modify, distribute.
Part of the Hybrid Agent Architecture. Built for agents that improve over time.
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